{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "862014b8",
   "metadata": {},
   "source": [
    "# Questão 5 - Rede SOM analisando dados de países\n",
    "Considere a tabela de índices de desenvolvimento de países (Fonte ONU- 2002, Livro – Análise de dados através de métodos de estatística multivariada – Sueli A. Mingoti) abaixo. Gere o mapa SOM e com isto identifique os clusters existentes, i.e., o países com características mais similares.\n",
    "\n",
    "| Países          | Expectativa de vida | Educação | PIB  | Estabilidade política |\n",
    "|:---------------:|:------------------:|:--------:|:----:|:--------------------:|\n",
    "| Reino Unido     | 0.88               | 0.99     | 0.91 | 1.10                 |\n",
    "| Austrália       | 0.90               | 0.99     | 0.93 | 1.26                 |\n",
    "| Canadá          | 0.90               | 0.98     | 0.94 | 1.24                 |\n",
    "| Estados Unidos  | 0.87               | 0.98     | 0.97 | 1.18                 |\n",
    "| Japão           | 0.93               | 0.93     | 0.93 | 1.20                 |\n",
    "| França          | 0.89               | 0.97     | 0.92 | 1.04                 |\n",
    "| Cingapura       | 0.88               | 0.87     | 0.91 | 1.41                 |\n",
    "| Argentina       | 0.81               | 0.92     | 0.80 | 0.55                 |\n",
    "| Uruguai         | 0.82               | 0.92     | 0.75 | 1.05                 |\n",
    "| Cuba            | 0.85               | 0.90     | 0.64 | 0.07                 |\n",
    "| Colômbia        | 0.77               | 0.85     | 0.69 | -1.36                |\n",
    "| Brasil          | 0.71               | 0.83     | 0.72 | 0.47                 |\n",
    "| Paraguai        | 0.75               | 0.83     | 0.63 | -0.87                |\n",
    "| Egito           | 0.70               | 0.62     | 0.60 | 0.21                 |\n",
    "| Nigéria         | 0.44               | 0.58     | 0.37 | -1.36                |\n",
    "| Senegal         | 0.47               | 0.37     | 0.45 | -0.68                |\n",
    "| Serra Leoa      | 0.23               | 0.33     | 0.27 | -1.26                |\n",
    "| Angola          | 0.34               | 0.36     | 0.51 | -1.98                |\n",
    "| Etiópia         | 0.31               | 0.35     | 0.32 | -0.55                |\n",
    "| Moçambique      | 0.24               | 0.37     | 0.36 | 0.20                 |\n",
    "| China           | 0.76               | 0.80     | 0.61 | 0.39                 |\n",
    "| ...             | ...                | ...      | ...  | ...                  |\n",
    "| **Média**       | 0.69               | 0.75     | 0.68 | 0.16                 |\n",
    "| **Desvio padrão** | 0.24             | 0.249    | 0.229| 1.056                |"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e12cca2d",
   "metadata": {},
   "source": [
    "### Importando Bibliotecas Necessárias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b1347765",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: minisom in /Users/efrainmpp/Documents/Mestrado/Neural-Network-PPGEEC2321/.venv/lib/python3.9/site-packages (2.3.5)\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m25.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install minisom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "96c04aa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from minisom import MiniSom\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8255b307",
   "metadata": {},
   "source": [
    "### Leitura dos Dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "70a1ed55",
   "metadata": {},
   "outputs": [],
   "source": [
    "# writing the data\n",
    "countries = [\n",
    "    'Reino Unido', 'Austrália', 'Canadá', \n",
    "    'Estados Unidos', 'Japão', 'França', \n",
    "    'Cingapura', 'Argentina', 'Uruguai', \n",
    "    'Cuba', 'Colômbia','Brasil', \n",
    "    'Paraguai', 'Egito', 'Nigéria', \n",
    "    'Senegal', 'Serra Leoa', 'Angola', \n",
    "    'Etiópia', 'Moçambique', 'China'\n",
    "    ]\n",
    "    \n",
    "expected_life = [0.88, 0.90, 0.90, 0.87, 0.93, 0.89, 0.88, 0.81, 0.82, 0.85, 0.77, 0.71, 0.75, 0.70, 0.44, 0.47, 0.23, 0.34, 0.31, 0.24, 0.76]\n",
    "education = [0.99, 0.99, 0.98, 0.98, 0.93, 0.97, 0.87, 0.92, 0.92, 0.90, 0.85, 0.83, 0.83, 0.62, 0.58, 0.37, 0.33, 0.36, 0.35, 0.37, 0.80]\n",
    "pib = [0.91, 0.93, 0.94, 0.97, 0.93, 0.92, 0.91, 0.80, 0.75, 0.64, 0.69, 0.72, 0.63, 0.60, 0.37, 0.45, 0.27, 0.51, 0.32, 0.36, 0.80]\n",
    "politic = [1.10, 1.26, 1.24, 1.18, 1.20, 1.04, 1.41, 0.55, 1.05, 0.07, -1.36, 0.47, -0.87, 0.21, -1.36, -0.68, -1.26, -1.98, -0.55, 0.20, 0.39]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "81e7b92c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>expected_life</th>\n",
       "      <th>education</th>\n",
       "      <th>pib</th>\n",
       "      <th>politic</th>\n",
       "      <th>countries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.88</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.91</td>\n",
       "      <td>1.10</td>\n",
       "      <td>Reino Unido</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.90</td>\n",
       "      <td>0.99</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1.26</td>\n",
       "      <td>Austrália</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.90</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.94</td>\n",
       "      <td>1.24</td>\n",
       "      <td>Canadá</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.87</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.97</td>\n",
       "      <td>1.18</td>\n",
       "      <td>Estados Unidos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.93</td>\n",
       "      <td>0.93</td>\n",
       "      <td>0.93</td>\n",
       "      <td>1.20</td>\n",
       "      <td>Japão</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   expected_life  education   pib  politic       countries\n",
       "0           0.88       0.99  0.91     1.10     Reino Unido\n",
       "1           0.90       0.99  0.93     1.26       Austrália\n",
       "2           0.90       0.98  0.94     1.24          Canadá\n",
       "3           0.87       0.98  0.97     1.18  Estados Unidos\n",
       "4           0.93       0.93  0.93     1.20           Japão"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a dataframe\n",
    "df = pd.DataFrame({'expected_life': expected_life,\n",
    "                    'education': education, \n",
    "                    'pib': pib, \n",
    "                    'politic': politic,\n",
    "                    'countries': countries\n",
    "                    })\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "2352c42f",
   "metadata": {},
   "outputs": [],
   "source": [
    "expected_life_mean = 0.69\n",
    "expected_life_std = 0.24\n",
    "\n",
    "education_mean = 0.75\n",
    "education_std = 0.249\n",
    "\n",
    "pib_mean = 0.68\n",
    "pib_std = 0.229\n",
    "\n",
    "politic_mean = 0.16\n",
    "politic_std = 1.056"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71eb0e6b",
   "metadata": {},
   "source": [
    "### Inicializando e treinando rede SOM 10 x 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b33c3102",
   "metadata": {},
   "outputs": [],
   "source": [
    "neurons = 10\n",
    "input_len = 4\n",
    "# instantiate a minisom model \n",
    "som = MiniSom(neurons, neurons, input_len, sigma=1.0, learning_rate=0.5, topology='hexagonal', neighborhood_function='gaussian', random_seed=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d0d3b50a",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = df.drop('countries',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "87dd8eb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "iterations = 50000\n",
    "# train the model\n",
    "som.train(x.values, iterations)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68367907",
   "metadata": {},
   "source": [
    "### Plotando Resultadoss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e5a7aaa6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AALSaXUzr0yACAAAQNIgAAECraRDr0yACAAAQBEQAAACCEVMAAKDVjJjWp0EEAAAgCIgAAAAEI6YAAECrVVUnjpLnb4rmrBQAAIBepUEEAABaLm8SU3KjmCo1hQYRAACAICACAAAQjJgCAACt5j6I9WkQAQAACAIiAAAAwYgpAADQakZM69MgAgAAEDSIAABAq2kQ69MgAgAAEAREAAAAghFTAACg1aqqE0fJ8zdFc1YKAABArxIQAQAACEZMAQCAVrOLaX0aRAAAAIKACAAAQDBiCgAAtJoR0/o0iAAAAAQNIgAA0GoaxPo0iAAAAAQBEQAAgGDEFAAAaLmqcDdWpabQIAIAABAERAAAAPr2iOlu222XhgwZUnoZfdqdv/x16SU0xp8fNLr0Ehrh6H/4v0ovoRE+evDBpZfQGF/7t/9TegmNMKKrq/QSGmPBK6+UXkIjjNx2m9JLaIRXlrxWegmNsHTZstR0djGtT4MIAABA324QAQAAeoIGsT4NIgAAAEFABAAAIBgxBQAAWs2IaX0aRAAAAIKACAAAQDBiCgAAtJoR0/o0iAAAAAQBEQAAgGDEFAAAaLWq6sRR8vxN0ZyVAgAA0Ks0iAAAQKvZpKY+DSIAAABBQAQAACAYMQUAAFqu7IhpSkZMAQAAaBgBEQAAgGDEFAAAaLk84mnEtA4NIgAAAEGDCAAAtJr7INanQQQAACAIiAAAAAQjpgAAQKtVVSeOkudviuasFAAAgF4lIAIAABCMmAIAAK1mF9P6NIgAAAAEDSIAANBqGsT6NIgAAAAEAREAAIBgxBQAAGg1I6b1aRABAAAIAiIAAADBiCkAALAJjJiW68YqI6YAAAA0jYAIAABAMGIKAAC0ml1M69MgAgAAEDSIAABAy+UGr2SLV6Wm0CACAAAQBEQAAACCEVMAAKDVbFJTnwYRAACAICACAAAQjJgCAACtVnWqOEqevyk0iAAAAAQNIgAA0Go2qalPgwgAAEAQEAEAAAhGTAEAgFYzYlqfBhEAAIAgIAIAABCMmAIAAK1mxLQ+DSIAAABBQAQAACAYMQUAAFrNiGl9GkQAAACCBhEAAGi1qrPiKHn+pmjQUgEAAOhNAiIAAADBiCkAANBueZOYkhvFVDapAQAAoGF6JSA+88wz6eMf/3jadttt06BBg9K+++6bHnzwwd44FQAAQCtNmzYtjRo1Kg0cODCNGzcuPfDAA2/6+hdffDGdeuqpaYcddkgDBgxI73nPe9KPfvSjsiOmL7zwQjr00EPT4Ycfnn784x+n7bbbLj3++ONp66237ulTAQAAtPI+iLfcckuaPHlymj59eoTDq666Kk2YMCE9+uijafvtt1/r9UuWLEl//ud/Hn/2b//2b2mnnXZKTz/9dNpqq63KBsTLL788jRw5Ml1//fWrntttt916+jQAAACtdeWVV6ZJkyalk08+OR7noHj77ben6667Lp177rlrvT4//6c//Sn94he/SJtvvnk8l9vH4iOmP/jBD9LYsWPTxz72sUivBxxwQLr22mvX+/rFixenBQsWdDsAAAB6SpV/VQWPtKJBXDP35Cy0LrkNnDVrVho/fvyq5zqdTjyeOXPmenPYIYccEiOmw4cPT/vss0+69NJL09KlS8sGxCeffDJdc801aY899kg/+clP0t///d+n008/PX3nO99Z5+unTp2aurq6Vh25fQQAAGibkSNHdss+OQuty/PPPx/BLge91eXHc+fOXW8Oy6Ol+e/l6w7PO++89OUvfzldcsklZUdMly1bFg1iTqtZbhAffvjhqEQnTpy41uunTJkSs7Ur5SSdv3AvLHopvdZpznawJSya/1LpJTTG7T9/8wt6WWHmD9b9Eym622+/w0svoTFKXu/RJAtefaX0EhrjwFEuW6njtaXLSi+hEYYOGlR6Cc3w2mulV9Aac+bMSUOHDl31OG8k05M5LE9wfvOb30z9+vVLY8aMic1Dv/jFL6YLLrigXEDMO+bstdde3Z5773vfm7773e+u8/X5i9KTXxgAAIC+uEnN0KFDuwXE9Rk2bFiEvHnz5nV7Pj8eMWLEenNYvvYw/73Vc1huHPPIav/+/cuMmOYdTPPOOqt77LHH0q677trTpwIAAGid/v37RwM4Y8aMbg1hfpyvM1xfDnviiSfidavnsBwc64bDXgmIZ511VrrvvvtixDQv8KabboqaM18sCQAAwFvLl+HlzT7zXi6/+93vYm+XRYsWrdrV9MQTT4zL9VbKf553MT3jjDMiGOYdT3Mm29Ac1uMjpgcddFC67bbbYrGf//zn4xYX+Z4dxx9/fE+fCgAA4C1VnSqOkuffUMccc0x67rnn0vnnnx9joqNHj0533HHHqo1rZs+eHTubrpT3ccmbhObCbr/99ov7IOaweM4555QNiNlHPvKROAAAANg4p512Whzrcvfdd6/1XB4/zdOcb0ePj5gCAADQTL3SIAIAAPQZhXcxTQ267ZMGEQAAgKBBBAAAWq2v3AexCTSIAAAABAERAACAYMQUAABotTzhaY+aejSIAAAABAERAACAYMQUAABoNzOmtWkQAQAACBpEAACg1apOFUfJ8zeFBhEAAIAgIAIAABCMmAIAAJvAHjUFR0yr1BgaRAAAAIKACAAAQDBiCgAAtFoeLy07YlqlptAgAgAAEDSIAABAq2kQ69MgAgAAEAREAAAAghFTAACg1YyY1qdBBAAAIAiIAAAABCOmAABAq1WdKo6S528KDSIAAABBQAQAACAYMQUAAFotbyJaciPRqjkTphpEAAAAVtAgAgAAreY+iPVpEAEAAAgCIgAAAMGIKQAA0HKFd6lJRkwBAABoGAERAACAYMQUAABoNbuY1qdBBAAAIGgQAQCAVqs6VRwlz98UGkQAAACCgAgAAEAwYgoAALSaTWrq0yACAAAQBEQAAACCEVMAAKDVjJjWp0EEAAAgCIgAAAAEI6YAAECrGTGtT4MIAABA0CACAACtlgu8kiVe1ZwCUYMIAADACgIiAAAAwYgpAADQbp1qxVHy/A2hQQQAACAIiAAAAAQjpgAAQKu5D2J9GkQAAACCBhEAAGi3wg1i0iACAADQNAIiAAAAwYgpAADQajapqU+DCAAAQBAQAQAA6NsjptsNGZKGDB1aehl92na7bF96CY0xeMCA0ktohP/11/+r9BIaYcwRB5ZeQmNccurppZfQCBd965rSS2iMsbu9q/QSGmHg5puXXkIjLF++vPQSGqENXycjpvVpEAEAAOjbDSIAAEBPqDpVHCXP3xQaRAAAAIKACAAAQDBiCgAAtFreI6bsJjWpMTSIAAAABAERAACAYMQUAADYBEZMy56/KTSIAAAABAERAACAYMQUAABoucIzpqk5M6YaRAAAAIIGEQAAaLV8D8Sy90GsUlNoEAEAAAgCIgAAAMGIKQAA0GpVp4qj5PmbQoMIAABAEBABAAAIRkwBAIBWs4tpfRpEAAAAggYRAABoNQ1ifRpEAAAAgoAIAABAMGIKAAC0mhHT+jSIAAAABAERAACAYMQUAABoNSOm9WkQAQAACAIiAAAAwYgpAADQalVnxVHy/E3RoKUCAADQmzSIAABAu+VNYkpuFFPZpAYAAICGERABAAAIRkwBAIBWcx/E+jSIAAAABAERAACAYMQUAABoNSOm9WkQAQAACBpEAACg1TSI9WkQAQAACAIiAAAAwYgpAADQalWniqPk+ZtCgwgAAEAQEAEAAAhGTAEAgFazi2l9GkQAAACCgAgAAEAwYgoAALRb4RHTZMQUAACAptEgAgAArZb7u6IFYmoODSIAAABBQAQAACAYMQUAAFqt6lRxlDx/U2gQAQAACAIiAAAAwYgpAADQbnkLU/dBrEWDCAAAQNAgAgAArVZVVRwlz98UGkQAAACCgAgAAEAwYgoAAGwCe9SUHDFNjaFBBAAAIAiIAAAAvDMB8bLLLos698wzz+ztUwEAAKx3F9OSx8aYNm1aGjVqVBo4cGAaN25ceuCBB2r9vZtvvjnOefTRR/etgPjLX/4yfeMb30j77bdfb54GAACgVW655ZY0efLkdMEFF6SHHnoo7b///mnChAnp2WeffdO/94c//CGdffbZ6f3vf/9GnbfXAuJLL72Ujj/++HTttdemrbfeurdOAwAA8KaqTlX82FBXXnllmjRpUjr55JPTXnvtlaZPn5622GKLdN1116337yxdujQy2EUXXZTe9a53pT4VEE899dR05JFHpvHjx7/p6xYvXpwWLFjQ7QAAAGibBWvknpyF1mXJkiVp1qxZ3bJUp9OJxzNnzlzvP//zn/982n777dPf/u3fbvQaeyUg5pnXXINOnTr1LV+bX9PV1bXqGDlyZG8sCQAAoKiRI0d2yz7ry0vPP/98tIHDhw/v9nx+PHfu3HX+nXvvvTd9+9vfjgnOPnUfxDlz5qQzzjgj3XnnnXEx5VuZMmVKzNaulJN0/sL97OHfpUGDB/f08lrlyLEHll4CLfP6u5eWXkIjfO/n95VeQmMsW/Z66SU0wogdhpVeQmMM6t+/9BIaoV/HRvV19O/Xr/QSGmHpgAGp6d7ORjE9YeW5c1YaOnToqucH9NDXduHChemEE06IcDhs2LC+FRBzFZovnDzwwP8/vOT0e88996Srr746atR+q/2fMX9ReuoLAwAA0FcNHTq0W0BcnxzycmaaN29et+fz4xEjRqz1+t///vexOc1RRx216rlly5bF75tttll69NFH0+67714mIH7oQx9Kv/3tb7s9ly+s3HPPPdM555zTLRwCAADQXf/+/dOYMWPSjBkzVt2qIge+/Pi0005b49UpstaaGexzn/tcNItf+cpXNugyvh4PiEOGDEn77LNPt+cGDx6ctt1227WeBwAA6G15wrPghGnamHPny/AmTpyYxo4dmw4++OB01VVXpUWLFkX5lp144olpp512iusY86V9a2atrbbaKn7f0AzW4wERAACAt+eYY45Jzz33XDr//PNjY5rRo0enO+64Y9XGNbNnz46dTXvaOxIQ77777nfiNAAAAK1x2mmnrXOktE7GuuGGGzbqnBpEAACg1frKLqZNYA9kAAAAggYRAABotybuUlOIBhEAAIAgIAIAABCMmAIAAK1Wdao4Sp6/KTSIAAAABAERAACAYMQUAABoNfdBrE+DCAAAQNAgAgAAraZBrE+DCAAAQBAQAQAACEZMAQCAVjNiWp8GEQAAgCAgAgAAEIyYAgAArValwiOmyYgpAAAADSMgAgAAEIyYAgAArVZ1Vhwlz98UDVoqAAAAvUmDCAAAtJr7INanQQQAACAIiAAAAAQjpgAAQLvlEc+SY56VEVMAAAAaRkAEAAAgGDEFAABazS6m9WkQAQAACBpEAACg3Qo3iEmDCAAAQNMIiAAAAAQjpgAAQKtVnSqOkudvCg0iAAAAQUAEAAAgGDEFAABazX0Q69MgAgAAEDSIAABAq2kQ69MgAgAAEAREAAAAghFTAACg1fKEZ8kpz6o5E6YaRAAAAFYQEAEAAAhGTAEAgHYzY1qbBhEAAIAgIAIAABCMmAIAAK1WdfJRFT1/UzRoqQAAAPQmDSIAANBqVVXFUfL8TaFBBAAAIAiIAAAABCOmAABAqxkxrU+DCAAAQBAQAQAACEZMAQCAVjNiWp8GEQAAgKBBBAAAWk2DWJ8GEQAAgCAgAgAAEIyYAgAA7R8x7RgxrUODCAAAQBAQAQAACEZMAQCAVssTniWnPKvmTJj23YC48/bD0uAttyy9jD7t9gcfKr2ExnjXjsNLL6ER5r/8SuklNEKTriMo7W8mTS69hEb4/e+eLr2ExvjAnn9WegmNMHDz/qWX0Aj3//73pZfQCIsWLiy9BN5BRkwBAADo2w0iAABAjzBjWpsGEQAAgKBBBAAA2n8fxIItXqVBBAAAoGkERAAAAIIRUwAAoNWMmNanQQQAACAIiAAAAAQjpgAAQKtVnSqOkudvCg0iAAAAQYMIAAC0mk1q6tMgAgAAEAREAAAAghFTAACg1YyY1qdBBAAAIAiIAAAABCOmAABAqxkxrU+DCAAAQNAgAgAA7VblFq/s+ZtCgwgAAEAQEAEAAAhGTAEAgHbrVCuOkudvCA0iAAAAQUAEAAAgGDEFAABazX0Q69MgAgAAEAREAAAAghFTAACg1YyY1qdBBAAAIGgQAQCAVtMg1qdBBAAAIAiIAAAABCOmAABAq3WqKo6S528KDSIAAABBQAQAACAYMQUAAFotD3gW3cU0NYcGEQAAgKBBBAAAWs0mNfVpEAEAAAgCIgAAAMGIKQAA0Gp5wrPklGfVnAlTDSIAAAArCIgAAAAEI6YAAECrVW/8Knn+ptAgAgAAEAREAAAAghFTAACg1fKN6kverL7ToG1MNYgAAAAEDSIAANBqVVXFUfL8TaFBBAAAIAiIAAAABCOmAABAqxkxrU+DCAAAQBAQAQAACEZMAQCAVnMfxPo0iAAAAAQNIgAA0Go2qalPgwgAAEAQEAEAAAhGTAEAgFbLI54lN4qpjJgCAADQNAIiAAAAvRMQp06dmg466KA0ZMiQtP3226ejjz46Pfrooz19GgAAgFryhGfpY2NMmzYtjRo1Kg0cODCNGzcuPfDAA+t97bXXXpve//73p6233jqO8ePHv+nr37GA+LOf/Sydeuqp6b777kt33nlneu2119IRRxyRFi1a1NOnAgAAaKVbbrklTZ48OV1wwQXpoYceSvvvv3+aMGFCevbZZ9f5+rvvvjsdd9xx6ac//WmaOXNmGjlyZOSwZ555puwmNXfccUe3xzfccEM0ibNmzUof+MAHevp0AAAArXPllVemSZMmpZNPPjkeT58+Pd1+++3puuuuS+eee+5ar7/xxhu7Pf7Wt76Vvvvd76YZM2akE088se9cgzh//vz4fZtttuntUwEAAKyl6gO/NsSSJUuiYMtjoit1Op14nNvBOl5++eWY5tzQHNart7lYtmxZOvPMM9Ohhx6a9tlnn3W+ZvHixXGstGDBgt5cEgAAQBEL1sg6AwYMiGNNzz//fFq6dGkaPnx4t+fz40ceeaTWuc4555y04447dguZxQNivhbx4YcfTvfee++bbmpz0UUXrfX81ltskbYcPLg3l9d4z22xsPQSGuOp/1n3rDbdbTl4UOklNMLS114vvYTG2HXvXUovoRGO+MDBpZfQGA8++VTpJTTCPf/Phm9MsSna/YDdSy+hEV5pwV4incL3Qey8ce58XeDq8vWFF154YY+f77LLLks333xzXJeYN7jpEwHxtNNOSz/84Q/TPffck3beeef1vm7KlClx8eXqqXrNLxwAAEDTzZkzJw0dOnTV43W1h9mwYcNSv3790rx587o9nx+PGDHiTc/xpS99KQLif/zHf6T99ttvg9fY49cgLl++PMLhbbfdlu6666602267venr8xclf5FWPwAAANpm6Bq5Z30BsX///mnMmDGxwczql+/lx4cccsh6//lXXHFFuvjii2Pj0LFjx27UGjfrjbHSm266KX3/+9+PeyHOnTs3nu/q6kqDBhlfAwAA3llVVcVR8vwbKk9ZTpw4MYLewQcfnK666qq4deDKXU3zzqQ77bRTXLKXXX755en888+PLJbvnbgyh2255ZZxFAuI11xzTfz+wQ9+sNvz119/fTrppJN6+nQAAACtc8wxx6TnnnsuQl8Oe6NHj45mcOXGNbNnz46dTVfPYXn3049+9KNv6zrHzXpjxBQAAIC3J1+6l491yRvQrO4Pf/hD6gm9uospAABAaU0cMS2lxzepAQAAoJk0iAAAQKv1lfsgNoEGEQAAgCAgAgAAEIyYAgAArWaTmvo0iAAAAAQBEQAAgGDEFAAAaDUjpvVpEAEAAAgaRAAAoNU61Yqj5PmbQoMIAABAEBABAAAIRkwBAIBWq974VfL8TaFBBAAAIAiIAAAABCOmAABAq3WqKo6S528KDSIAAABBQAQAACAYMQUAAFotD3hWBcc8q9QcGkQAAACCBhEAAGi13B4WbRCr5nSIGkQAAACCgAgAAEAwYgoAALRaHvEseS/CyogpAAAATSMgAgAAEIyYAgAArWYX0/o0iAAAAAQNIgAA0GoaxPo0iAAAAAQBEQAAgGDEFAAAaLVOteIoef6m0CACAAAQBEQAAACCEVMAAKDVqjd+lTx/U2gQAQAACAIiAAAAwYgpAADQap2qiqPk+ZtCgwgAAEDQIAIAAK1WVVUcJc/fFBpEAAAAgoAIAABAMGIKAAC0mhHT+jSIAAAABAERAACAYMQUAABoNfdBrE+DCAAAQNAgAgAArWaTmvo0iAAAAAQBEQAAgGDEFAAAaDUjpvVpEAEAAAgCIgAAAMGIKQAA0GqdasVR8vxNoUEEAAAgaBABAIBWq974VfL8TaFBBAAAIAiIAAAABCOmAABAuxW+D2JyH0QAAACaRkAEAAAgGDEFAABarVNVcZQ8f1P02YC4z8iRaejQoaWX0aftPnx46SU0xv/7wgull9AIw7u6Si+hEZ72/73a7p3129JLaIRtt9yy9BIaY+Grr5ZeQiN0+hkSq2P/d40qvYRGeGnhwtJL4B3kuwcAAAB9u0EEAADoCVXhXUyrBo2YahABAAAIGkQAAKDVbFJTnwYRAACAICACAAAQjJgCAACtZpOa+jSIAAAABAERAACAYMQUAABotTzgWXTENDWHBhEAAICgQQQAAFqtU604Sp6/KTSIAAAABAERAACAYMQUAABoteqNXyXP3xQaRAAAAIKACAAAQDBiCgAAtFq+B2LR+yBWRkwBAABoGAERAACAYMQUAABotU5VxVHy/E2hQQQAACBoEAEAgFazSU19GkQAAACCgAgAAEAwYgoAALSaEdP6NIgAAAAEAREAAIBgxBQAAGg190GsT4MIAABA0CACAADtVniTmqRBBAAAoGkERAAAAIIRUwAAoNU61Yqj5PmbQoMIAABAEBABAAAIRkwBAIBWq974VfL8TaFBBAAAIAiIAAAABCOmAABAq1VVFUfJ8zeFBhEAAICgQQQAAFqtU1VxlDx/U2gQAQAACAIiAAAAwYgpAADQajapqU+DCAAAQBAQAQAACEZMAQCAVjNiWp8GEQAAgKBBBAAAWs19EOvTIAIAABAERAAAAIIRUwAAoNVsUlOfBhEAAIAgIAIAABCMmAIAAK3WqVYcJc/fFBpEAAAAggYRAABoteqNXyXP3xQaRAAAAIKACAAAQDBiCgAAtJr7INanQQQAACAIiAAAAAQjpgAAQKt1qiqOkudPm3qDOG3atDRq1Kg0cODANG7cuPTAAw/01qkAAADoqwHxlltuSZMnT04XXHBBeuihh9L++++fJkyYkJ599tneOB0AAAB9NSBeeeWVadKkSenkk09Oe+21V5o+fXraYost0nXXXdcbpwMAAHjLXUxLHpvsNYhLlixJs2bNSlOmTFn1XKfTSePHj08zZ85c6/WLFy+OY6X58+fH7wsWLOjppbXOotW+bry5lxYuLL2ERhjUoG9eJXk/1ffKyy+XXkIjLPTvvNoW+f9fLYtffaX0EhrB9/N6Fr30Uvy+fPny1FSls8WCBn2f7/GA+Pzzz6elS5em4cOHd3s+P37kkUfWev3UqVPTRRddtNbzI0eO7OmlAUCf9OnSC4BN1GXnll5Bs/zxj39MXV1dqUn69++fRowY0SeyxYgRI2I9fV3xXUxz05ivV1zpxRdfTLvuumuaPXt2496A9E35Jzb5m8KcOXPS0KFDSy+HFvCeoqd5T9HTvKfoSXnCb5dddknbbLNNapq8YeZTTz0VU46l9e/fP9azyQXEYcOGpX79+qV58+Z1ez4/zql5TQMGDIhjTTkc+oZGT8rvJ+8pepL3FD3Ne4qe5j1FT8qXjTVRDmVNCGZ9Rac3kvGYMWPSjBkzVj23bNmyeHzIIYf09OkAAADoyyOmeWR04sSJaezYsenggw9OV111VVq0aFHsagoAAMAmFBCPOeaY9Nxzz6Xzzz8/zZ07N40ePTrdcccda21csy553DTfP3FdY6ewMbyn6GneU/Q07yl6mvcUPcn7adNSLW/yfrUAAAD0mGZeaQoAAECPExABAAAIAiIAAABBQAQAAKBvBsRp06alUaNGxc0sx40blx544IHSS6Khpk6dmg466KA0ZMiQtP3226ejjz46Pfroo6WXRUtcdtllqaqqdOaZZ5ZeCg32zDPPpI9//ONp2223TYMGDUr77rtvevDBB0svi4ZaunRpOu+889Juu+0W76fdd989XXzxxcl+hNR1zz33pKOOOirtuOOO8e+4733ve93+PL+X8l0Kdthhh3iPjR8/Pj3++OPF1ssmEBBvueWWuIdi3kb3oYceSvvvv3+aMGFCevbZZ0svjQb62c9+lk499dR03333pTvvvDO99tpr6Ygjjoh7csLb8ctf/jJ94xvfSPvtt1/ppdBgL7zwQjr00EPT5ptvnn784x+n//7v/05f/vKX09Zbb116aTTU5Zdfnq655pp09dVXp9/97nfx+Iorrkhf+9rXSi+NhsifkfLn71zYrEt+P331q19N06dPT/fff38aPHhwfFZ/9dVX3/G1sonc5iI3hrnxyd/YsmXLlqWRI0emf/zHf0znnntu6eXRcPnenLlJzMHxAx/4QOnl0FAvvfRSOvDAA9PXv/71dMkll8R9Xq+66qrSy6KB8r/X/vM//zP9/Oc/L70UWuIjH/lI3HP629/+9qrn/uqv/iqann/9138tujaaJzeIt912W0xgZTky5Gbx05/+dDr77LPjufnz58d77oYbbkjHHnts4RXTugZxyZIladasWVFVr9TpdOLxzJkzi66NdsjfxLJtttmm9FJosNxKH3nkkd2+V8HG+MEPfpDGjh2bPvaxj8UPrw444IB07bXXll4WDfa+970vzZgxIz322GPx+De/+U26995704c//OHSS6MFnnrqqTR37txu//7r6uqKgsdn9XbZLPURzz//fMzO559CrC4/fuSRR4qti3bIbXS+ViyPc+2zzz6ll0ND3XzzzTH+nkdM4e168sknYxwwX1rx2c9+Nt5Xp59+eurfv3+aOHFi6eXR0FZ6wYIFac8990z9+vWLz1Vf+MIX0vHHH196abRADofZuj6rr/wz2qHPBETo7dbn4Ycfjp+kwsaYM2dOOuOMM+J61ryJFvTED65yg3jppZfG49wg5u9T+doeAZGNceutt6Ybb7wx3XTTTWnvvfdOv/71r+OHo3ks0HsKaNyI6bBhw+KnXfPmzev2fH48YsSIYuui+U477bT0wx/+MP30pz9NO++8c+nl0FB5BD5vmJWvP9xss83iyNez5ov183/PP6mHDZF3Adxrr726Pffe9743zZ49u9iaaLbPfOYz0SLma8HyjrgnnHBCOuuss2JXb3i7Vn4e91m9/fpMQMwjNWPGjInZ+dV/upofH3LIIUXXRjPli6lzOMwXWN91112x7TdsrA996EPpt7/9bfxEfuWR2588upX/e/4BF2yIPPK+5q138rVju+66a7E10Wwvv/xy7N+wuvy9KX+egrcrf47KQXD1z+p5pDnvZuqzerv0qRHTfB1GHoHIH7oOPvjg2Bkwb7d78sknl14aDR0rzWM23//+9+NeiCvn4/MF1XlHN9gQ+T205vWreXvvfP8617WyMXKzkzcVySOmf/3Xfx33/f3mN78ZB2yMfP+6fM3hLrvsEiOmv/rVr9KVV16ZTjnllNJLo0E7dT/xxBPdNqbJPwTNG/zl91UeWc47eO+xxx4RGPN9N/MI88qdTmmHPnWbiyzf4uKLX/xifJjP28fn8a28OxJszPbM63L99denk0466R1fD+3zwQ9+0G0ueFvy+PuUKVPiRtP5w1b+QemkSZNKL4uGWrhwYXxgz5MzeSQ+f3A/7rjj4sbmeVIL3srdd9+dDj/88LWezwVOvpVFjg35fuX5B1kvvvhiOuyww+K2T+95z3uKrJdNJCACAACwiV+DCAAAQFkCIgAAAEFABAAAIAiIAAAABAERAACAICACAAAQBEQAAACCgAgAAEAQEAEAAAgCIgAAAEFABAAAIAiIAAAApOz/A4TzeabTsp4MAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the data\n",
    "plt.figure(figsize=(12, 9))\n",
    "plt.pcolor(som.distance_map().T, cmap='bone_r')\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8c7484a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "wmap = {}\n",
    "im = 0\n",
    "\n",
    "for x, t in zip(x.values, df.countries.values):\n",
    "  w = som.winner(x)\n",
    "  wmap[w] = im\n",
    "  plt.text(\n",
    "      w[0], w[1], str(t),\n",
    "      rotation=20,\n",
    "      c=np.random.rand(3,),\n",
    "      fontdict={'weight': 'bold', 'size': 11}\n",
    "  )\n",
    "  im = im+1\n",
    "\n",
    "plt.axis([-0.5,9.5,-0.5,9.5])\n",
    "plt.xticks(range(10))\n",
    "plt.yticks(range(10))\n",
    "plt.grid()\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
